结直肠癌预后生物标志物的生物信息学挖掘与实验验证

Bioinformatics mining and experimental validation of prognostic biomarkers in colorectal cancer.

作者信息

Huang Feng, Alshehade Salah A, Zhao Wei Guo, Li Zhuo Ya, Fong Jung Yin, Ng Chin Tat, Chen Li, Chinnappan Sasikala, Alshawsh Mohammed Abdullah, Venkatachalam Karthikkumar, Selvaraja Malarvili

机构信息

Faculty of Pharmaceutical Sciences, UCSI University, 56000, Kuala Lumpur, Malaysia.

Guangdong Provincial Key Laboratory of Chinese Medicine Ingredients and Gut Microbiomics, School of Pharmacy, Shenzhen University Medical School, Shenzhen University, Shenzhen, 518055, China.

出版信息

Discov Oncol. 2025 Aug 22;16(1):1596. doi: 10.1007/s12672-025-03301-9.

Abstract

Colorectal cancer (CRC) is a prevalent condition with increasing incidence and mortality rates. The identification of robust prognostic gene signatures remains an unmet clinical need in CRC treatment. In this study, data from the GEO and TCGA databases were utilized to identify 2,779 upregulated and 2,629 downregulated genes in CRC tissues compared to adjacent normal tissues. WGCNA analysis highlighted the MEbrown module, which comprised 1,639 genes that exhibited strong correlations with CRC progression. Subsequently, an intersection analysis was conducted to further refine the candidate gene set, resulting in the selection of 926 differentially expressed CRC-related genes for subsequent analysis. Through univariate Cox regression, LASSO regularization, and multivariate Cox regression, a five-gene prognostic signature (TIMP1, PCOLCE2, MEIS2, HDC, CXCL13) was established, demonstrating consistent predictive accuracy in external (GSE32323) and internal validation cohorts. Mutational profiling showed predominant missense mutations across signature genes, with TIMP1 exhibiting the highest variant allele frequency. Functional enrichment analysis linked TIMP1 to critical CRC pathways including type I interferon receptor binding, oxidative phosphorylation, and Notch signaling pathways. High expression of TIMP1 was associated with poor prognosis in patients with CRC. Additionally, using siRNA technology, the impact of TIMP1 on cellular proliferation, metastasis and apoptosis in CRC cell lines (HCT116 and HT29) was investigated, showing that TIMP1 knockdown significantly inhibited CRC cell proliferation, metastasis, and promoted apoptosis. These experimental results were consistent with the conclusions drawn from the bioinformatics analysis. This research presents a prognostic risk model for CRC, further highlights TIMP1 as a potential biomarker and therapeutic target for the disease.

摘要

结直肠癌(CRC)是一种普遍存在的疾病,其发病率和死亡率呈上升趋势。确定强大的预后基因特征仍然是CRC治疗中尚未满足的临床需求。在本研究中,利用来自GEO和TCGA数据库的数据,鉴定出与相邻正常组织相比,CRC组织中2779个上调基因和2629个下调基因。加权基因共表达网络分析(WGCNA)突出了MEbrown模块,该模块包含1639个与CRC进展呈强相关的基因。随后,进行了交集分析以进一步优化候选基因集,从而选择了926个差异表达的CRC相关基因用于后续分析。通过单变量Cox回归、LASSO正则化和多变量Cox回归,建立了一个五基因预后特征(TIMP1、PCOLCE2、MEIS2、HDC、CXCL13),在外部(GSE32323)和内部验证队列中显示出一致的预测准确性。突变分析表明,特征基因中主要为错义突变,TIMP1表现出最高的变异等位基因频率。功能富集分析将TIMP1与关键的CRC通路联系起来,包括I型干扰素受体结合、氧化磷酸化和Notch信号通路。TIMP1的高表达与CRC患者的不良预后相关。此外,使用小干扰RNA(siRNA)技术,研究了TIMP1对CRC细胞系(HCT116和HT29)中细胞增殖、转移和凋亡的影响,结果表明TIMP1基因敲低显著抑制CRC细胞增殖、转移并促进凋亡。这些实验结果与生物信息学分析得出的结论一致。本研究提出了一种CRC的预后风险模型,进一步突出了TIMP1作为该疾病潜在生物标志物和治疗靶点的作用。

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